Triple
T23491575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayers-Allen |
E570689
|
entity |
| Predicate | componentSurname |
P5298
|
FINISHED |
| Object | Ayers |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ayers | Statement: [Ayers-Allen, componentSurname, Ayers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayers Context triple: [Ayers-Allen, componentSurname, Ayers]
-
A.
Ayers
chosen
Ayers is a surname most notably associated with Roy Ayers, the influential American jazz-funk vibraphonist and composer.
-
B.
Ayers-Allen
Ayers-Allen is the hyphenated surname of American actress Phylicia Rashad, used earlier in her career before she adopted her current professional name.
-
C.
Ayres
Ayres is a surname most notably associated with American actor Lew Ayres, famed for his role in the film "All Quiet on the Western Front."
-
D.
Whigham
Whigham is a surname most notably associated with American actor Shea Whigham, known for his character roles in film and television.
-
E.
Tilghman
Tilghman is a surname most notably associated with Shirley M. Tilghman, a prominent molecular biologist and former president of Princeton University.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7dc631c819099027e3a1c755a66 |
completed | April 29, 2026, 6:40 a.m. |
Created at: April 17, 2026, 6:04 p.m.